Sequence Kernel Association Test of Multiple Continuous Phenotypes

Genetic Epidemiology

Volumn 40, Issue 2, 2016, Pages 91-100

  Wu, Baolin ^a   Pankow, James S ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

Author keywords

GWAS; Rare variant; Score statistic; SKAT

Indexed keywords

TRANSCRIPTION FACTOR YAP1; PHOSPHOPROTEIN; SIGNAL TRANSDUCING ADAPTOR PROTEIN; YAP1 (YES-ASSOCIATED) PROTEIN, HUMAN;

ARTICLE; DIABETES MELLITUS; EXOME; GENETIC ASSOCIATION; GENETIC TRAIT; GENETIC VARIABILITY; HUMAN; PHENOTYPE; SEQUENCE KERNEL ASSOCIATION TEST; SIMULATION; STATISTICAL ANALYSIS; YAP1 GENE; ALGORITHM; ANALYSIS OF VARIANCE; ATHEROSCLEROSIS; BIOLOGICAL MODEL; GENETIC ASSOCIATION STUDY; GENETIC PREDISPOSITION; GENETICS; PROCEDURES; QUANTITATIVE TRAIT;

ADAPTOR PROTEINS, SIGNAL TRANSDUCING; ALGORITHMS; ANALYSIS OF VARIANCE; ATHEROSCLEROSIS; EXOME; GENETIC ASSOCIATION STUDIES; GENETIC PREDISPOSITION TO DISEASE; HUMANS; MODELS, GENETIC; PHENOTYPE; PHOSPHOPROTEINS; QUANTITATIVE TRAIT, HERITABLE;

EID: 84955456708     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.21945     Document Type: Article

References (37)

1. Avery CL, He Q, North KE, Ambite JL, Boerwinkle E, Fornage M, Hindorff LA, Kooperberg C, Meigs JB, Pankow JS, and others. 2011. A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains. PLoS Genet 7(10):e1002322.
2. Chen H, Lumley T, Brody J, Heard-Costa NL, Fox CS, Cupples LA, Dupuis J. 2014. Sequence kernel association test for survival traits. Genet Epidemiol 38(3):191-197.
3. Chen W, Wang W, Zhu B, Guo H, Sun Y, Ming J, Shen N, Li Z, Wang Z, Liu L, and others. 2013. A functional variant rs1820453 in YAP1 and breast cancer risk in Chinese population. PLoS ONE 8(11):e79056.
4. 2 random variables. Appl Stat 29(3):323-333.
5. Dixit D, Ghildiyal R, Anto NP, Sen E. 2014. Chaetocin-induced ROS-mediated apoptosis involves ATM-YAP1 axis and JNK-dependent inhibition of glucose metabolism. Cell Death Dis 5(5):e1212.
6. Ferreira MAR, Purcell SM. 2009. A multivariate test of association. Bioinformatics 25(1):132-133.
7. Grove ML, Yu B, Cochran BJ, Haritunians T, Bis JC, Taylor KD, Hansen M, Borecki IB, Cupples LA, Fornage M, and others. 2013. Best practices and joint calling of the HumanExome BeadChip: the CHARGE consortium. PloS One 8(7):e68095.
8. He Q, Avery CL, Lin DY. 2013. A general framework for association tests with multivariate traits in large-scale genomics studies. Genet Epidemiol 37(8):759-767.
9. Hua WY, Ghosh D. 2015. Equivalence of kernel machine regression and kernel distance covariance for multidimensional phenotype association studies. Biometrics 71(3):812-820.
10. Kuonen D. 1999. Saddlepoint approximations for distributions of quadratic forms in normal variables. Biometrika 86(4):929-935.
11. Lee S, Wu MC, Lin X. 2012. Optimal tests for rare variant effects in sequencing association studies. Biostatistics 13(4):762-775.
12. Li T, Zhao H, Zhao X, Zhang B, Cui L, Shi Y, Li G, Wang P, Chen ZJ. 2012. Identification of YAP1 as a novel susceptibility gene for polycystic ovary syndrome. J Med Genet 49(4):254-257.
13. Lin DY, Tang ZZ. 2011. A general framework for detecting disease associations with rare variants in sequencing studies. Am J Hum Genet 89(3):354-367.
14. Liu H, Tang Y, Zhang HH. 2009a. A new chi-square approximation to the distribution of non-negative definite quadratic forms in non-central normal variables. Comput Stat Data Anal 53(4):853-856.
15. Liu J, Pei Y, Papasian CJ, Deng HW. 2009b. Bivariate association analyses for the mixture of continuous and binary traits with the use of extended generalized estimating equations. Genet Epidemiol 33(3):217-227.
16. Louwers YV, Stolk L, Uitterlinden AG, Laven JSE. 2013. Cross-ethnic meta-analysis of genetic variants for polycystic ovary syndrome. J Clin Endocrinol Metab 98(12):E2006-E2012.
17. Madsen BE, Browning SR. 2009. A groupwise association test for rare mutations using a weighted sum statistic. PLOS Genet 5(2):e1000384.
18. Maity A, Sullivan PF, Tzeng JY. 2012. Multivariate phenotype association analysis by marker-set kernel machine regression. Genet Epidemiol 36(7):686-695.
19. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, McCarthy MI, Ramos EM, Cardon LR, Chakravarti A, and others. 2009. Finding the missing heritability of complex diseases. Nature 461(7265):747-753.
20. Morgenthaler S, Thilly WG. 2007. A strategy to discover genes that carry multi-allelic or mono-allelic risk for common diseases: a cohort allelic sums test (CAST). Mutat Res 615(1-2):28-56.
21. Morris AP, Zeggini E. 2010. An evaluation of statistical approaches to rare variant analysis in genetic association studies. Genet Epidemiol 34(2):188-193.
22. Neale BM, Rivas MA, Voight BF, Altshuler D, Devlin B, Orho-Melander M, Kathiresan S, Purcell SM, Roeder K, Daly MJ. 2011. Testing for an unusual distribution of rare variants. PLoS Genet 7(3):e1001322.
23. OReilly PF, Hoggart CJ, Pomyen Y, Calboli FCF, Elliott P, Jarvelin MR, Coin LJM. 2012. MultiPhen: joint model of multiple phenotypes can increase discovery in GWAS. PLoS ONE 7(5):e34861.
24. Price AL, Kryukov GV, de Bakker PIW, Purcell SM, Staples J, Wei LJ, Sunyaev SR. 2010. Pooled association tests for rare variants in exon-resequencing studies. Am J Hum Genet 86(6):832-838.
25. Rasmussen-Torvik LJ, Alonso A, Li M, Kao W, Kattgen A, Yan Y, Couper D, Boerwinkle E, Bielinski SJ, Pankow JS. 2010. Impact of repeated measures and sample selection on genome-wide association studies of fasting glucose. Genet Epidemiol 34(7):665-673.
26. Schaffner SF, Foo C, Gabriel S, Reich D, Daly MJ, Altshuler D. 2005. Calibrating a coalescent simulation of human genome sequence variation. Genome Res 15(11):1576-1583.
27. Schifano E, Li L, Christiani D, Lin X. 2013. Genome-wide association analysis for multiple continuous secondary phenotypes. Am J Human Genetics 92(5):744-759.
28. Solovieff N, Cotsapas C, Lee PH, Purcell SM, Smoller JW. 2013. Pleiotropy in complex traits: challenges and strategies. Nat Rev Genet 14(7):483-495.
29. Stephens M. 2013. A unified framework for association analysis with multiple related phenotypes. PLoS ONE 8(7):e65245.
30. The ARIC Investigators. 1989. The atherosclerosis risk in communities (aric) study: design and objectives. Am J Epidemiol 129(4):687-702.
31. van der Sluis S, Posthuma D, Dolan CV. 2013. TATES: efficient multivariate genotype-phenotype analysis for genome-wide association studies. PLoS Genet 9(1):e1003235.
32. Wu B, Pankow JS. 2015. Statistical methods for association tests of multiple continuous traits in genome-wide association studies. Ann Hum Genet 79(4):282-293.
33. Wu B, Pankow JS, Guan W. 2015. Sequence kernel association analysis of rare variant set based on the marginal regression model for binary traits. Genet Epidemiol 39(6):399-405.
34. Wu C, Xu B, Yuan P, Miao X, Liu Y, Guan Y, Yu D, Xu J, Zhang T, Shen H, and others. 2010. Genome-wide interrogation identifies YAP1 variants associated with survival of small-cell lung cancer patients. Cancer Res 70(23):9721-9729.
35. Wu MC, Kraft P, Epstein MP, Taylor DM, Chanock SJ, Hunter DJ, Lin X. 2010. Powerful SNP-Set analysis for case-control genome-wide association studies. Am J Hum Genet 86(6):929-942.
36. Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X. 2011. Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet 89(1):82-93.
37. Yang Q, Wu H, Guo CY, Fox CS, 2010. Analyze multivariate phenotypes in genetic association studies by combining univariate association tests. Genet Epidemiol 34(5):444-454.